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MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images
The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of f...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5974206/ https://www.ncbi.nlm.nih.gov/pubmed/29875639 http://dx.doi.org/10.3389/fnana.2018.00037 |
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author | Varando, Gherardo Benavides-Piccione, Ruth Muñoz, Alberto Kastanauskaite, Asta Bielza, Concha Larrañaga, Pedro DeFelipe, Javier |
author_facet | Varando, Gherardo Benavides-Piccione, Ruth Muñoz, Alberto Kastanauskaite, Asta Bielza, Concha Larrañaga, Pedro DeFelipe, Javier |
author_sort | Varando, Gherardo |
collection | PubMed |
description | The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections. |
format | Online Article Text |
id | pubmed-5974206 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59742062018-06-06 MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images Varando, Gherardo Benavides-Piccione, Ruth Muñoz, Alberto Kastanauskaite, Asta Bielza, Concha Larrañaga, Pedro DeFelipe, Javier Front Neuroanat Neuroscience The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections. Frontiers Media S.A. 2018-05-23 /pmc/articles/PMC5974206/ /pubmed/29875639 http://dx.doi.org/10.3389/fnana.2018.00037 Text en Copyright © 2018 Varando, Benavides-Piccione, Muñoz, Kastanauskaite, Bielza, Larrañaga and DeFelipe. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Varando, Gherardo Benavides-Piccione, Ruth Muñoz, Alberto Kastanauskaite, Asta Bielza, Concha Larrañaga, Pedro DeFelipe, Javier MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images |
title | MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images |
title_full | MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images |
title_fullStr | MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images |
title_full_unstemmed | MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images |
title_short | MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images |
title_sort | multimap: a tool to automatically extract and analyse spatial microscopic data from large stacks of confocal microscopy images |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5974206/ https://www.ncbi.nlm.nih.gov/pubmed/29875639 http://dx.doi.org/10.3389/fnana.2018.00037 |
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